AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a specific approach to reach the same goal.

This year’s winner of Best use of machine learning/AI, ActiveViam stood out for delivering a practical, production-ready ...

The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular biomarkers, including those from OCT angiography, according to data ...

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

To Integrate AI into existing workflows successfully requires experimentation and adaptation. The tools don't replace how you ...

For decades, soil management has relied on sparse field sampling and averaged recommendations. While effective in relatively uniform landscapes, this approach breaks down in real-world fields where ...

A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing ...

Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...